With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Aim To study the effects of lentinan(LNT)on the metabolism of dendritic cells(DCs)by metabonomics, and uncover the potential mechanism of its regulation of DC function. Methods DC2.4 cells were co-incubated with LNT for 24 h, and the activity of the cells was detected by thiazolyl blue tetrazolium bromide(MTT)assay. The contents of interleukin-6(IL-6), tumor necrosis factorα(TNF-α)and interleukin-12(IL-12)in supernatant were detected by enzyme-linked immunosorbent assay(ELISA). The metabolic general changes of DC2.4 cells were detected by Ultra performance liquid chromatography-quadrupole time-of-flight mass spectrometry(UPLC-QTOF/MS), and the differential metabolites were analyzed by multi-distance covariates and bioinformatics, partial least squares-discriminant analysis(PLS-DA). Finally, metabolic pathway analysis was performed by MetaboAnalyst 5.0. Results LNT did not significantly inhibit the activity of DC2.4 cells at the dose of 25100 mg·L-1. LNT(100 mg·L-1)could significantly stimulate the secretion of IL-6, TNF-α and IL-12 in DC2.4 cells. 20 differential metabolites were identified in DC2.4 cells after being stimulated by LNT(100 mg·L-1), which involved 25 metabolic pathways including urea cycle, arginine and proline metabolism. Conclusion The regulation of LNT on DC function involves a variety of amino acid metabolism.

Objective:To analyze the incidence and prognosis of epilepsy in frontotemporal lobe glioma.Methods:The clinical data of 208 patients with frontotemporal lobe gliomas in Sanbo Brain Hospital Capital Medical University from 2019 to 2021 were analyzed retrospectively. According to the 2016 World Health Organization (WHO) classification of tumors of the central nervous system, the incidence of epilepsy, Modified Rankin Scale (MRS) score, and Engel Outcome Scale of patients with different grades of tumors were calculated.Results:Among all the patients with frontotemporal lobe gliomas, there was more males than females, and it was more common in the 40 -59 age group. The incidence of epilepsy associated with WHO grade Ⅰand Ⅱ glioma was 100.0% (33/33) and 60.9% (14/23), respectively, while that of WHO grade Ⅳ glioma was 19.0%(19/100). The average follow-up time was (22 ± 9) months. During the follow-up period, the incidence of WHO grade Ⅰ, Ⅱ and Ⅲ glioma-related epilepsy decreased significantly. There was no significant difference in the incidence of glioma-related epilepsy between the total and subtotal resection groups ( P>0.05). There was no statistical correlation between the side of tumor occurrence and the occurrence of epilepsy ( P>0.05), also between the gene phenotype and the occurrence of epilepsy ( P>0.05). There was no significant difference in the Engel Outcome Scale among different grades of gliomas ( P>0.05). The prognosis of patients with Engel Outcome Scale Class 1 was significantly better than that of other grades. Conclusions:The incidence of glioma-related epilepsy is negatively correlated with tumor grade. Age and sex are risk factors for glioma-related epilepsy. The incidence of postoperative epilepsy in patients with low grade glioma is significantly lower than that in patients with high grade glioma, and the prognosis is better. However, there is no significant difference in the Engel Outcome Scale among different grades of gliomas.

OBJECTIVE: To investigate the effect of silencing CD46 and desmoglein 2 (DSG2) in host A549 cells on the entry of human adenovirus type 3 (HAdV-3) and type 7 (HAdV-7) and host cell secretion of inflammatory cytokines. METHODS: RNA interference technique was use to silence the expression of CD46 or DSG2 in human epithelial alveolar A549 cells as the host cells of HAdV-3 or HAdV-7. The binding of the viruses with CD46 and DSG2 were observed with immunofluorescence staining at 0.5 and 1 h after viral infection. The viral load in the host cells was determined with qRT-PCR, and IL-8 secretion level was measured using ELISA. RESULTS: In infected A549 cells, immunofluorescent staining revealed colocalization of HAdV-3 and HAdV-37 with their receptors CD46 and DSG2 at 0.5 h and 2 h after infection, and the copy number of the viruses increased progressively after the infection in a time-dependent manner. In A549 cells with CD46 silencing, the virus titers were significantly lower at 2, 6, 12 and 24 h postinfection in comparison with the cells without gene silencing; the virus titers were also significantly decreased in the cells with DSG2 silencing. The secretion level of IL-8 increased significantly in A549 cells without siRNA transfection following infection with HAdV-3 and HAdV-7 (P < 0.0001), but decreased significantly in cells with CD46 and DSG2 silencing (P < 0.0001). CONCLUSION HAdV-3 and HAdV-7 enter host cells by binding to their receptors CD46 and DSG2, and virus titer and cytokines release increase with infection time. Silencing CD46 and DSG2 can inhibit virus entry and cytokine IL-8 production in host cells.
A549 Cells ; Adenoviruses, Human/metabolism* ; Desmoglein 2/metabolism* ; Humans ; Interleukin-8 ; Membrane Cofactor Protein/genetics* ; RNA, Small Interfering

The nervous system and the immune system are relatively independent but interactional, and neuro-immune regulation is very important for the respiratory system to resist external harmful stimuli and to maintain homeostasis. Neuro-immune interaction is involved in the occurrence and development of respiratory diseases, and is essential for monitoring and modulating inflammation and tissue repair. This article summaries the neuro-immune regulation of respiratory system and discusses its role in respiratory diseases, aiming to provide a theoretical basis for further understanding the crosstalk between the nervous and immune systems, to explore the underlying mechanism in respiratory diseases, and to provide new thoughts for the prevention and treatment of respiratory diseases.
Homeostasis ; Humans ; Immune System ; Inflammation ; Nervous System ; Neuroimmunomodulation ; Respiration Disorders

OBJECTIVES: To compare the application effect of microwave digestion - vacuum filtration - automated scanning electron microscopy (MD-VF-Auto SEM) method and plankton gene multiplex PCR system in the diagnosis of drowning. METHODS: Lung, liver and kidney tissue of 10 non-drowning cases and 50 drowning cases were prepared for further MD-VF-Auto SEM method analysis and plankton gene multiplex PCR system analysis. The positive detection rate of the two methods in each tissue was calculated. RESULTS: The positive rate of the MD-VF-Auto SEM method detecting diatoms in drowning cases was 100%, and few diatoms were detected in the liver and kidney tissues of 6 non-drowning cases. By using the plankton gene multiplex PCR system, the diatom positive rate of drowning cases was 84%, and all the non-drowning cases were negative. There were significant differences in the positive rate of the liver, kidney tissues between MD-VF-Auto SEM method and plankton gene multiplex PCR system (P<0.05), as well as the total positive rate of cases. However, no significant differences were found in the positive rates of lung tissues (P>0.05). CONCLUSIONS MD-VF-Auto SEM method is more sensitive than plankton gene multiplex PCR system in diatom test. But the plankton gene multiplex PCR system can also detect plankton other than diatoms. Combination of the two methods can provide a more reliable basis for the diagnosis of drowning.
Diatoms/genetics* ; Drowning/diagnosis* ; Humans ; Liver ; Lung ; Microscopy, Electron, Scanning ; Multiplex Polymerase Chain Reaction ; Plankton/genetics*

This study aimed to explore the anti-depressant components of Rehmanniae Radix and its action mechanism based on network pharmacology combined with molecular docking. The main components of Rehmanniae Radix were identified by ultra-high performance liquid chromatography-quadrupole/Orbitrap high resolution mass spectrometry(UPLC-Q-Orbitrap HRMS), and the related targets were predicted using SwissTargetPrediction. Following the collection of depression-related targets from GeneCards, OMIM and TTD, a protein-protein interaction(PPI) network was constructed using STRING. GO and KEGG pathway enrichment analysis was performed by Metascape. Cytoscape 3.7.2 was used to construct the networks of "components-targets-disease" and "components-targets-pathways", based on which the key targets and their corresponding components were obtained and then preliminarily verified by molecular docking. Rehmanniae Radix contained 85 components including iridoids, ionones, and phenylethanoid glycosides. The results of network analysis showed that the main anti-depressant components of Rehmanniae Radix were catalpol, melittoside, genameside C, gardoside, 6-O-p-coumaroyl ajugol, genipin-1-gentiobioside, jiocarotenoside A1, neo-rehmannioside, rehmannioside C, jionoside C, jionoside D, verbascoside, rehmannioside, cistanoside F, and leucosceptoside A, corresponding to the following 16 core anti-depression targets: AKT1, ALB, IL6, APP, MAPK1, CXCL8, VEGFA, TNF, HSP90 AA1, SIRT1, CNR1, CTNNB1, OPRM1, DRD2, ESR1, and SLC6 A4. As revealed by molecular docking, hydrogen bonding and hydrophobicity might be the main action forms. The key anti-depression targets of Rehmanniae Radix were concentrated in 24 signaling pathways, including neuroactive ligand-receptor interaction, neurodegenerative disease-multiple diseases pathway, phosphatidylinositol 3-kinase/protein kinase B pathway, serotonergic synapse, and Alzheimer's disease.
Drugs, Chinese Herbal/pharmacology* ; Humans ; Molecular Docking Simulation ; Network Pharmacology ; Neurodegenerative Diseases ; Plant Extracts ; Rehmannia

Objective:To compare the effects of different processing techniques on the chemical constituents of Aurantii Fructus for screening the dominant decoction pieces. Method:UPLC-Q/TOF-MS was used to detect the chemical constituents of Aurantii Fructus, chromatography separation was achieved on an ACQUITY UPLC BEH C₁₈ column (2.1 mm×100 mm, 1.7 μm), and gradient elution was performed with 0.1% formic acid aqueous solution (A)-0.1% formic acid acetonitrile solution (B) as mobile phase (0-10 min, 5%-35%B; 10-18 min, 35%-75%B; 18-21 min, 75%-100%B; 21-24 min, 100%B; 24-24.1 min, 100%-5%B; 24.1-28 min, 5%B). Data acquisition was carried out in electrospray ionization (ESI) under the positive ion mode, the scanning range was m/z 50-1 200. The chemical constituents in methanol extract of Aurantii Fructus were identified according to reference substance, relative molecular weight, mass spectrometric cleavage rule and literature information. SIMCA-P 13.0 software was used to establish principal component analysis (PCA) model and partial least squares-discriminant analysis (PLS-DA) model of Aurantii Fructus processed products, PCA score plot, PLS-DA loading plot and variable importance in the protection (VIP) values were obtained to screen the material basis for the main differences before and after processing of Aurantii Fructus. Result:A total of 54 chemical components were identified by UPLC-Q/TOF-MS. PCA indicated that there were significant differences among different groups of Aurantii Fructus processed by different methods. A total of 14 chemical components with VIP value >1 were screened by PLS-DA as the main chemical markers for the differences before and after processing, including hesperidin, poncirin, narirutin, etc. The comprehensive weighted score showed that the content of effective components in Aurantii Fructus processed with honey bran was the highest. Conclusion:The contents of chemical constituents in Aurantii Fructus before and after processing are significantly changed. Flavonoids are the most important compounds to distinguish different processed products of Aurantii Fructus. Aurantii Fructus processed with honey bran is the dominant variety.